• Title/Summary/Keyword: Market anomaly

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The Weekend and January Effect in the Ghana Stock Market (가나 증권시장의 주말 효과와 1월 효과)

  • Ahialey, Joseph Kwaku;Kang, Ho-Jung
    • The Journal of the Korea Contents Association
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    • v.15 no.8
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    • pp.460-472
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    • 2015
  • The aim of this study is to analyze the Weekend and January effect in the Ghana Stock Exchange (GSE) using daily closing prices of GSE-All Share Index (ASI) and Composite Index (CI) between the period of January 4th, 2005 and December 31st, 2013. The dataset covers the period of 2005 to 2010 (6 years) for the ASI and 2011 to 2013 (3 years) for the CI. The following results are obtained based on a parametric regression using dummy variables. First, no weekly effect or anomaly is documented for both GSE-ASI and GSE-CI. Second, market abnormalities are captured for both GSE-ASI and GSE-CI over their respective entire periods. However, no consistent April effect is found for ASI when the period was segregated into two periods of three years. The April effect is uncovered for the GSE-ASI at 5% significant level while the January effect is found for the GSE-CI at 1% significant level.

Margin and Funding Liquidity: An Empirical Analysis on the Covered Interest Parity in Korea (우리나라 외환시장의 차익거래 유인에 대한 분석)

  • Jeong, Daehee
    • KDI Journal of Economic Policy
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    • v.34 no.1
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    • pp.29-52
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    • 2012
  • During the global financial turmoil in 2007-2008, deviation from the covered interest parity (CIP) between the Korean won and US dollar through the foreign exchange swap has escalated in its magnitude beyond 1,000bp in November 2008, and it still persists around 100bp level. In this paper, we examine a newly developed margin based asset pricing model using Kalman filter approach and show that the escalation of the CIP deviation is found to be significantly related to the global dollar funding illiquidity and country-specific funding conditions. Furthermore, we find evidence that the poor funding conditions (or higher margins) are driven by the general money market illiquidity and may lead to higher funding illiquidity, which suggests the reinforcing effects of the liquidity spiral. We also show that the supply of dollar liquidity and improved funding conditions help alleviate the deviations from the parity, however the persistent anomaly is found to be related to the high level of volatility in the FX swap market.

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Application of Highland Kimchi Cabbage Status Map for Growth Monitoring based on Unmanned Aerial Vehicle

  • Na, Sang-Il;Park, Chan-Won;Lee, Kyung-Do
    • Korean Journal of Soil Science and Fertilizer
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    • v.49 no.5
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    • pp.469-479
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    • 2016
  • Kimchi cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. In particular Kimchi cabbages in a highland area are very sensitive to the fluctuations in supply and demand. Yield variability due to growth conditions dictates the market fluctuations of Kimchi cabbage price. This study was carried out to understand the distribution of the highland Kimchi cabbage growth status in Anbandeok. Anbandeok area in Gangneung, Gangwon-do, Korea is one of the main producing districts of highland Kimchi cabbage. The highland Kimchi cabbage status map of each growth factor was obtained from unmanned aerial vehicle (UAV) imagery and field survey data. Six status maps include UAVRGB image map, normalized difference vegetation index (NDVI) distribution/anomaly map, Crop distribution map, Planting/Harvest distribution map, Growth parameter map and Growth disorder map. As a result, the highland Kimchi cabbage status maps from May 31 to Sep. 6 in 2016 were presented to show spatial variability in the field. The benefits of the highland Kimchi cabbage status map can be summarized as follows: crop growth monitoring, reference for field observations and survey, the relative comparison of the growth condition in field scale, evaluation of growth in comparison of average year, change detection of annual crops or planting areas, abandoned fields monitoring, prediction of harvest season etc.

A survey and categorization of anomaly detection in online games (온라인 게임에서의 이상 징후 탐지 기법 조사 및 분류)

  • Kwak, Byung Il;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.5
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    • pp.1097-1114
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    • 2015
  • As the online game market grows, illegal activities such as cheating play using game bots or game hack programs, running private servers, hacking game companies' system and network, and account theft are also increasing. There are various security measures for online games to prevent illegal activities. However, the current security measures are not enough to prevent all highly evolving game attacks and frauds. Some security measure can do harm game players usability, game companies need to develop usable security measure that is well fit to game genre and contents design. In this study, we surveyed the recent trend of various security measure applied in online games. This research also classified illegal activities and their related countermeasure for detection and prevention.

ANNs on Co-occurrence Matrices for Mobile Malware Detection

  • Xiao, Xi;Wang, Zhenlong;Li, Qi;Li, Qing;Jiang, Yong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2736-2754
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    • 2015
  • Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

Does Market Performance Influence Credit Risk? (기업의 시장성과는 신용위험에 영향을 미치는가?)

  • Lim, Hyoung-Joo;Mali, Dafydd
    • The Journal of the Korea Contents Association
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    • v.16 no.3
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    • pp.81-90
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    • 2016
  • This study aims to investigate the association between stock performance and credit ratings, and credit rating changes using a sample of 1,691 KRX firm-years that acquire equity in the form of long-term bonds from 2002 to 2013. Previous U.S. literature is mixed with regard to the relation between credit ratings and stock price. On one hand, there is evidence of a positive relation between credit ratings and stock prices, an anomaly established in U.S. studies. On the other hand, the CAPM model suggests a negative relation between stock prices and credit ratings, implying that investors expect financial rewards for bearing additional risk. To our knowledge, we are the first to examine the relationship between stock price and default risk proxied by credit ratings in period t+1. We find a negative (positive) relation between credit ratings (risk) in period t+1 and stock returns in period t, suggesting that credit rating agencies do not consider stock returns as a metric with the potential to influence default risk. Our results suggest that market participants may prefer firms with higher credit risk because of expected higher returns.

A Study on Detection Technique of Anomaly Signal for Financial Loan Fraud Based on Social Network Analysis (소셜 네트워크 분석 기반의 금융회사 불법대출 이상징후 탐지기법에 관한 연구)

  • Wi, Choong-Ki;Kim, Hyoung-Joong;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.22 no.4
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    • pp.851-868
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    • 2012
  • After the financial crisis in 2008, the financial market still seems to be unstable with expanding the insolvency of the financial companies' real estate project financing loan in the aftermath of the lasted real estate recession. Especially after the illegal actions of people's financial institutions disclosed, while increased the anxiety of economic subjects about financial markets and weighted in the confusion of financial markets, the potential risk for the overall national economy is increasing. Thus as economic recession prolongs, the people's financial institutions having a weak profit structure and financing ability commit illegal acts in a variety of ways in order to conceal insolvent assets. Especially it is hard to find the loans of shareholder and the same borrower sharing credit risk in advance because most of them usually use a third-party's name bank account. Therefore, in order to effectively detect the fraud under other's name, it is necessary to analyze by clustering the borrowers high-related to a particular borrower through an analysis of association between the whole borrowers. In this paper, we introduce Analysis Techniques for detecting financial loan frauds in advance through an analysis of association between the whole borrowers by extending SNA(social network analysis) which is being studied by focused on sociology recently to the forensic accounting field of the financial frauds. Also this technique introduced in this pager will be very useful to regulatory authorities or law enforcement agencies at the field inspection or investigation.

The Method of Feature Selection for Anomaly Detection in Bitcoin Network Transaction (비트코인 네트워크 트랜잭션 이상 탐지를 위한 특징 선택 방법)

  • Baek, Ui-Jun;Shin, Mu-Gon;Jee, Se-Hyun;Park, Jee-Tae;Kim, Myung-Sup
    • KNOM Review
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    • v.21 no.2
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    • pp.18-25
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    • 2018
  • Since the development of block-chain technology by Satoshi Nakamoto and Bitcoin pioneered a new cryptocurrency market, a number of scale of cryptocurrency have emerged. There are crimes taking place using the anonymity and vulnerabilities of block-chain technology, and many studies are underway to improve vulnerability and prevent crime. However, they are not enough to detect users who commit crimes. Therefore, it is very important to detect abnormal behavior such as money laundering and stealing cryptocurrency from the network. In this paper, the characteristics of the transactions and user graphs in the Bitcoin network are collected and statistical information is extracted from them and presented as plots on the log scale. Finally, we analyze visualized plots according to the Densification Power Law and Power Law Degree, as a result, present features appropriate for detection of anomalies involving abnormal transactions and abnormal users in the Bitcoin network.

A Study on The Day of Week Effect in International Stock Markets : Focusing on the Settlement and Clearing Procedure (세계증권시장에서 주중 요일별 수익률 효과 분석의 연구 : 결제청산과정을 중심으로)

  • Kim, Kyung-Won
    • The Korean Journal of Financial Management
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    • v.20 no.2
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    • pp.201-234
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    • 2003
  • This paper examines the day of the week effect focusing on the effect of the settlement procedures on the stock price in seven major international stock markets. Settlement dates or procedures may have an effect on rate of return distributions in international stock markets. Those Settlement procedures are different among various international stock markets. Furthermore, several international stock markets change their systems of settlement procedures. On the New York stock exchanges, stock transactions are settled in five business days after the transaction. However, they changed settlement procedures from five business days to three business days from 1995. Those settlement procedures on the London stock exchanges and the Paris stock exchanges were changes from the fixed settlement date systems to the fixed settlement lag systems. Thus, this paper examines the effect of the changes in settlement procedures on the stock price in several stock markets. I found that changes of settlement dates or procedures have an effect on the rate of return distributions for specific days in some stock markets. This paper also examines the day of the week effect for seven international stock markets. I found that strong weekend effect before the period of 1990. However, the weekend effect has disappeared during the period from 1990 to 2002 in international stock markets.

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Implementation of Security Information and Event Management for Realtime Anomaly Detection and Visualization (실시간 이상 행위 탐지 및 시각화 작업을 위한 보안 정보 관리 시스템 구현)

  • Kim, Nam Gyun;Park, Sang Seon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.5
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    • pp.303-314
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    • 2018
  • In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.